TrialDesignConditionalDunnett: Conditional Dunnett Design

In rpact: Confirmatory Adaptive Clinical Trial Design and Analysis

Conditional Dunnett Design

Description

Trial design for conditional Dunnett tests.

Details

This object should not be created directly; use getDesignConditionalDunnett with suitable arguments to create a conditional Dunnett test design.

Fields

kMax

The maximum number of stages K. Is a numeric vector of length 1 containing a whole number.

alpha

The significance level alpha, default is 0.025. Is a numeric vector of length 1 containing a value between 0 and 1.

stages

The stage numbers of the trial. Is a numeric vector of length kMax containing whole numbers.

informationRates

The information rates (that must be fixed prior to the trial), default is (1:kMax) / kMax. Is a numeric vector of length kMax containing values between 0 and 1.

userAlphaSpending

The user defined alpha spending. Contains the cumulative alpha-spending (type I error rate) up to each interim stage. Is a numeric vector of length kMax containing values between 0 and 1.

criticalValues

The critical values for each stage of the trial. Is a numeric vector of length kMax.

stageLevels

The adjusted significance levels to reach significance in a group sequential design. Is a numeric vector of length kMax containing values between 0 and 1.

alphaSpent

The cumulative alpha spent at each stage. Is a numeric vector of length kMax containing values between 0 and 1.

bindingFutility

If TRUE, the calculation of the critical values is affected by the futility bounds and the futility threshold is binding in the sense that the study must be stopped if the futility condition was reached (default is FALSE) Is a logical vector of length 1.

tolerance

The numerical tolerance, default is 1e-06. Is a numeric vector of length 1.

informationAtInterim

The information to be expected at interim, default is informationAtInterim = 0.5. Is a numeric vector of length 1 containing a value between 0 and 1.

secondStageConditioning

The way the second stage p-values are calculated within the closed system of hypotheses. If FALSE, the unconditional adjusted p-values are used, otherwise conditional adjusted p-values are calculated. Is a logical vector of length 1.

sided

Describes if the alternative is one-sided (1) or two-sided (2). Is a numeric vector of length 1 containing a whole number.

See Also

getDesignConditionalDunnett for creating a conditional Dunnett test design.

rpact documentation built on July 9, 2023, 6:30 p.m.